Abstract
This paper presents an algorithm based on Kalman filtering approach that is used to estimate position and heading of a land vehicle. Source of data for the system are acquisition of low cost (Global Positioning System) GPS receiver, low cost (microelectromechanical systems) MEMS gyroscope and odometer sensor. The algorithm allows defining current position and heading of vehicle when GPS signal is unavailable. To demonstrate the estimation performance of algorithm the number of experiments was performed. As the result obtained data is described in this paper.
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